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When can Non-Inferiority Trials Establish Efficacy? FDA Explains With Guidance

The US Food and Drug Administration (FDA) on Monday finalized guidance to pharmaceutical and biotech sponsors looking for more advice on when non-inferiority studies demonstrating effectiveness of an investigational drug can provide interpretable results, how to choose the non-inferiority margin and how to test the non-inferiority hypothesis.

The 56-page guidance, which finalizes a draft from 2010 and supersedes the 2010 guidance known as "Antibacterial Drug Products: Use of Noninferiority Trials to Support Approval," includes four parts:

A general discussion of regulatory, study design, scientific and statistical issues associated with the use of non-inferiority studies to establish the effectiveness of a drug or biologic

A further discussion of some of the issues with these studies, including the statistical approaches used to determine the non-inferiority margin and to test for non-inferiority

Commonly asked questions about non-inferiority trials

Four examples of successful and unsuccessful efforts to define non-inferiority margins and test for non-inferiority

Background

Three of them — placebo, no treatment, and dose-response controlled trials — are trials that attempt to prove a drug is superior to the control. For the fourth kind, however, comparison with an active treatment, also known as active control, can be a means for the sponsor to show that the new drug is more effective than the control.

However, FDA notes that more commonly, the goal of such an active control study is to show that the difference between the new drug and active control is “small enough to allow the known effectiveness of the active control, based on its performance in past studies and the assumed effectiveness of the active control in the current study, to support the conclusion that the new test drug is also effective.”

But FDA explains that the ways to design and interpret the results of such active control studies to support a conclusion of effectiveness is challenging, particularly as the intent of an non-inferior trial is not to show that the new drug is equivalent to the control, but that it is not materially worse.

The critical difference between superiority and non-inferiority trials, according to FDA, “is that a properly designed and conducted superiority trial, if successful in showing a difference, is entirely interpretable without further assumptions (other than lack of bias) — that is, the result speaks for itself and requires no extra-study information. In contrast, the non-inferiority study is dependent on knowing something that is not measured in the study, namely, that the active control had its expected effect in the non-inferiority study. When this occurs, the trial is said to have assay sensitivity, defined as the ability to have shown a difference from placebo of a specified size.”

In addition, what FDA defines as a “successful” non-inferiority trial, is a trial that shows what appears to be an acceptably small difference between treatments, may or may not have had assay sensitivity and therefore may or may not support a conclusion that the test drug was effective.

“Thus, if the active control had no effect at all in the non-inferiority trial (i.e., did not have any of its expected effect), then even ruling out a very small difference between control and test drug is meaningless and provides no evidence that the test drug is effective,” FDA says. “In the absence of a placebo arm, knowing whether the trial had assay sensitivity relies heavily on external (not within-study) information, giving non-inferiority studies some of the characteristics of a historically controlled trial.”

FDA also makes clear that its regulations have recognized since 1985 that there's a need to know that the active control had its expected effect in the trial in order for a non-inferiority trial to be interpretable.

Reasons for Using a Non-Inferiority Design

The usual reason, according to FDA, for using such a study design instead of a superiority design is an ethical one (ie. it would not be ethical to use a placebo, or a no-treatment control, or a very low dose of an active drug because there is an effective treatment that provides a benefit to patients for the condition to be studied in the trial.)

However, FDA says there may be other reasons to include an active control, possibly in conjunction with a placebo control, either to compare treatments or to assess assay sensitivity.

“Caregivers, third party payers, and some regulatory authorities have increasingly placed an emphasis on the comparative effectiveness of treatments, leading to more studies that compare two treatments,” the guidance says. “Such studies can provide information about the clinical basis for comparative effectiveness claims, which may be helpful in assessing cost effectiveness of treatments. If a placebo group is included in addition to the active comparator, it becomes possible to judge whether the study could have distinguished treatments that differed substantially, e.g., active drug versus placebo.”

Number of Studies Needed

Ordinarily, with some exceptions allowed under the FDA Modernization Act of 1997, FDA expects that there will be more than one adequate and well-controlled study supporting effectiveness.

But in cases where there is uncertainty about the magnitude of the historical treatment effect because of variability or reliance on a single historical study, more than one non-inferiority study is usually needed to support effectiveness, FDA says.

And where the studies are of relatively modest size, there is usually no impediment to conducting more than one non-inferiority trial if that appears necessary.

“Conducting two trials that are very large (to have adequate statistical power), however, may be infeasible, and it is worth considering what might make a single trial persuasive. Generally, two considerations might do so: (1) availability of other relevant information and (2) a statistically persuasive result,” FDA says.

The guidance also features lengthy discussions on how to choose a non-inferiority margin and test the non-inferiority hypothesis, as well as more information on statistical uncertainties and the act of quantifying the active control effect.